In today's business and scientific world, color has become essential as a component of communication. Color facilitates the sharing of knowledge and ideas. Companies involved in the development of digital color print engines are continuously looking for ways to improve the total image quality of their products.
One of the elements that affect image quality is the ability to consistently produce the same quality image output on a printer from one day to another. Users have become accustomed to printers and copiers that produce high quality color and gray-scaled output. Users expect to be able to reproduce a color image with consistent quality on any compatible marking device. There is a commercial need for efficiently maintaining print color predictability, particularly as electronic marketing has placed more importance on the accurate representation of merchandise in illustrative print or display media.
Description of color, color perception, and psychological and physiological phenomena involving light, object and observer, including color measurements using spectrophotometers are described in R. W. G. Hunt, “The Reproduction of Color in Photography, Printing and Television”, 4th Ed., Fountain Press, Tolworth, England (1987) ISBN 0-8524-2356. Color correction and/or control should not be confused with color registration systems and sensors for insuring that colors are positioned properly, printed accurately, superposed correctly and/or adjacent to one another.
The functional models presented herein use a device independent color space to consistently track a set of target colors. L*a*b* are the CIE (Commission Internationale de I'Eclairage) color standards utilized in the modeling wherein L* defines lightness, a* corresponds to the red/green value, and b* denotes the amount of yellow/blue, which corresponds to the way people perceive color. A neutral color is a color where a*=b*=0.
Over time, the output of conventional marking devices drift or deviate from predetermined standards due to various factors which include environmental conditions (temperature, relative humidity, etc.), use patterns, type of media used (e.g., different paper types and paper batches, transparencies, etc.), variations in media, variations from original models used in initialization, wear, etc. When a marking device is originally initialized, and at intervals thereafter, it is calibrated and characterized to produce output as close as possible to a reference standard. However, the calibration and characterization process can be time consuming and expensive.
As an example, calibration and characterization of a conventional four-color CMYK (cyan, magenta, yellow, black) printer or copier involves at least the following processes: 1) generating a 3D Look-Up Table (LUT) for mapping device independent parameter space to CMY space; 2) executing a Gray Component Replacement/Under Color Removal (GCR/UCR) strategy to convert the CMY space parameters to CMYK space parameters which represent the colors of a typical four-color marking device; 3) constructing marking device Tone Reproduction Curves (TRCs) to account for marking device variability (normally done at the time of manufacturing or wherever the printer calibration and characterization process is involved); and 4) applying a suitable half-toning strategy to convert the CMYK continuous tone description obtained after using the 3D LUTs in steps 1 and 2 above and 1D LUTs in step 3 above, to the image, to a binary description (e.g., bits to be received by a raster output scanner or similar device for outputting the image). The first two steps above are generally grouped under printer characterization. The third step is normally called calibration for the purpose hereof. See, Henry R. Kang, “Color Technology for Electronic Imaging Devices”, ISBN 0-8194-2108-1, SPIE Optical Engineering Press, 1997.
In processing the image, one important step that accounts for variations in marking device output is TRC construction. TRCs are stored plots of an input parameter value versus an output parameter value for a particular color separation such as, C, M, Y, or K. A TRC is a monotonically increasing marking device function in input-output contone space or input-output density space or input-output byte space, or combinations thereof. In other words, a TRC indicates the value of the output parameter for a specific device that is used to reproduce the input parameter (if the input and output parameters are exactly equal then the inputs and outputs are expressed in the same coordinate space). Inaccuracies in TRC construction can lead to inaccuracies in color balancing and the 3D LUT.
Obtaining TRCs for a particular color marking engine is a calibration process, which can be constructed by printing predetermined target colors and measuring the printed target colors using insitu color sensors. Predetermined target colors can be printed as chronological jobs in the banner sheet/header sheet or else the target colors can be extracted from the customer image and measured either by measuring straight from the output image or by rendering subsets of customer colors as target color patches in banner and header pages. Using target colors and their measured counterparts, and by processing the measured colors, TRCs can be adjusted on-line at desired intervals or on request during system or color balance set ups.
Generally, obtaining 1D TRCs is associated with achieving neutral gray balance. Grayness is an indication of how “clean” a process color is compared to its theoretical ideal. Good gray has zero chroma (a*=b*=0). When equal amounts of cyan, magenta and yellow are printed on a white paper, a well balanced printer should produce a neutral gray of the same amount. Instead, a brownish color rather than a neutral gray may occur. The color reproduction system may not produce the desired gray due to various limitations on color pigments of the primaries and the internal processes of the print engine. To overcome this, gray balanced TRCs can be used as 1D LUTs to modulate the amount of cyan, magenta and yellow proportions depending on the state of the materials and the print engine.
The TRCs are obtained by printing large number of patches, mostly near neutral. In the color reproduction industry, colors are often measured using offline spectrophotometers and measured quantities are then modified, generally, by using model based algorithms to produce the desired gray balanced TRCs. Usually this process of printing and producing TRCs is iterated several times until satisfactory results are obtained. This type of approach is time consuming and expensive due to the use of machine models and offline spectrophotometer hardware.
Solutions to the foregoing color correction problems for a wide range of workflow practices are desired in this art. Printing and other enhancements are needed which enable customers to manipulate color documents by controlling color in ways that improve workflow and productivity.
One way of controlling any given color inside the printer gamut can be achieved iteratively by printing and measuring a color patch and varying CMYK/L*a*b* values to follow a desired target color. This often requires a gain matrix function in an adaptive closed loop controller. A sensitivity matrix can be used to calculate the gain matrix can be difficult to compute in the field when calibrating complex color reproduction and marking devices.
Accordingly, what is needed in this art are novel systems and methods heretofore unknown to this art for automatically determining a sensitivity matrix for adaptive color control in color marking devices capable of device independent color correction.